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Scientific workflows integrate data and computing interfaces as configurable, semi-automatic graphs to solve a scientific problem. Kepler is such a software system for designing, executing, reusing, evolving, archiving and sharing scientific workflows. Electron tomography (ET) enables high-resolution views of complex cellular structures, such as cytoskeletons, organelles, viruses and chromosomes. Imaging investigations produce large datasets. For instance, in Electron Tomography, the size of a 16 fold image tilt series is about 65 Gigabytes with each projection image including 4096 by 4096 pixels. When we use serial sections or montage technique for large field ET, the dataset will be even larger. For higher resolution images with multiple tilt series, the data size may be in terabyte range. Demands of mass data processing and complex algorithms require the integration of diverse codes into flexible software structures. This paper describes a workflow for Electron Tomography Programs in Kepler (EPiK). This EPiK workflow embeds the tracking process of IMOD, and realizes the main algorithms including filtered backprojection (FBP) from TxBR and iterative reconstruction methods. We have tested the three dimensional (3D) reconstruction process using EPiK on ET data. EPiK can be a potential toolkit for biology researchers with the advantage of logical viewing, easy handling, convenient sharing and future extensibility.

Environmental sensor networks are now commonly being deployed within environmental observatories and as components of smaller-scale ecological and environmental experiments. Effectively using data from these sensor networks presents technical challenges that are difficult for scientists to overcome, severely limiting the adoption of automated sensing technologies in environmental science. The Realtime Environment for Analytical Processing (REAP) is an NSF-funded project to address the technical challenges related to accessing and using heterogeneous sensor data from within the Kepler scientific workflow system. Using distinct use cases in terrestrial ecology and oceanography as motivating examples, we describe workflows and extensions to Kepler to stream and analyze data from observatory networks and archives. We focus on the use of two newly integrated data sources in Kepler: DataTurbine and OPeNDAP. Integrated access to both near real-time data streams and data archives from within Kepler facilitates both simple data exploration and sophisticated analysis and modeling with these data sources.

Modern web technologies facilitate the creation of high-quality data visualizations, and rich, interactive components across a wide variety of devices. Scientific workflow systems can greatly benefit from these technologies by giving scientists a better understanding of their data or model leading to new insights. While several projects have enabled web access to scientific workflow systems, they are primarily organized as a large portal server encapsulating the workflow engine. In this vision paper, we propose the design for Kepler WebView, a lightweight framework that integrates web technologies with the Kepler Scientific Workflow System. By embedding a web server in the Kepler process, Kepler WebView enables a wide variety of usage scenarios that would be difficult or impossible using the portal model. [ABSTRACT FROM AUTHOR]

Abstract: Scientific workflows integrate data and computing interfacesas configurable, semi-automatic graphs to solve a scientific problem. Kepler is such a software system for designing, executing, reusing, evolving, archiving and sharing scientific workflows. Electron tomography (ET) enables high-resolution views of complex cellular structures, such as cytoskeletons, organelles, viruses and chromosomes. Imaging investigations produce large datasets. For instance, in Electron Tomography, the size of a 16 fold image tilt series is about 65 Gigabytes with each projection image including 4096 by 4096 pixels. When we use serial sections or montage technique for large field ET, the dataset will be even larger. For higher resolution images with multiple tilt series, the data size may be in terabyte range. Demands of mass data processing and complex algorithms require the integration of diverse codes into flexible software structures. This paper describes a workflow for Electron Tomography Programs in Kepler (EPiK). This EPiKworkflow embeds the tracking process of IMOD, and realizes the main algorithms including filtered backprojection (FBP) from TxBR and iterative reconstruction methods. We have tested the three dimensional (3D) reconstruction process using EPiK on ET data. EPiK can be a potential toolkit for biology researchers with the advantage of logical viewing, easy handling, convenient sharing andfuture extensibility. [Copyright &y& Elsevier]

Abstract: We describe the development of automated workflows that support computed-aided drug discovery (CADD) and molecular dynamics (MD) simulations and are included as part of the National Biomedical Computation Resource (NBCR). The main workflow components include: file-management tasks, ligand force field parameterization, receptor-ligand molecular dynamics (MD) simulations, job submission, serial and parallel execution, and monitoring on relevant high-performance computing (HPC) resources, receptor structural clustering, virtual screening (VS), and statistical analyses of the VS results. The workflows aim to standardize simulation and analysis and promote best practices within the molecular simulation and CADD communities. Each component is developed as a stand-alone workflow, which should allow for easy integration into larger frameworks built suiting user needs, while remaining intuitive and easy to extend. [Copyright &y& Elsevier]

Abstract: Distributed Data-Parallel (DDP) patterns such as MapReduce have become increasingly popular as solutions to facilitate data-intensive applications, resulting in a number of systems supporting DDP workflows. Yet, applications or workflows built using these patterns are usually tightly-coupled with the underlying DDP execution engine they select. We present a framework for distributed data-parallel execution in the Kepler scientific workflow system that enables users to easily switch between different DDP execution engines. We describe a set of DDP actors based on DDP patterns and directors for DDP workflow executions within the presented framework. We demonstrate how DDP workflows can be easily composed in the Kepler graphic user interface through the reuse of these DDP actors and directors and how the generated DDP workflows can be executed in different distributed environments. Via a bioinformatics usecase, we discuss the usability of the proposed framework and validate its execution scalability. [Copyright &y& Elsevier]